Professor Rahman's research involves (1) low-level sensor development to capture observable low-level physical signals from our bodies and surrounding environments with high fidelity, (2) signal interpretation algorithm development to map these low-level physical signals to relevant biological and behavioral measurements, and (3) mobile computing to run these algorithms in low power and resource settings. His research is interdisciplinary and employs core concepts and theories from different domains including applied physics, embedded and mobile computing, signal processing, machine learning, health sciences and medicine. Professor Rahman's long-term research vision is to rethink the core physical mechanisms of existing health technologies and to impact the way we diagnose diseases, track and manage our health.